Tracking 3D Deformable Objects in Real Time

Tiago Silva, Luís Magalhães, Manuel Ferreira, Salik Ram Khanal, Jorge Silva

2022

Abstract

3D object tracking is a topic that has been widely studied for several years. Although there are already several robust solutions for tracking rigid objects, when it comes to deformable objects the problem increases in complexity. In recent years, there has been an increase in the use of Machine / Deep Learning techniques to solve problems in computer vision, including 3D object tracking. On the other hand, several low-cost devices (like Kinect) have appeared that allow obtaining RGB-D images, which, in addition to colour information, contain depth information. In this paper is proposed a 3D tracking approach for deformable objects that use Machine / Deep Learning techniques and have RGB-D images as input. Furthermore, our approach implements a tracking algorithm, increasing the object segmentation performance towards real time. Our tests were performed on a dataset acquired by ourselves and have obtained satisfactory results for the segmentation of the deformable object.

Paper Citation

in Harvard Style

Silva T., Magalhães L., Ferreira M., Khanal S. and Silva J. (2022). Tracking 3D Deformable Objects in Real Time. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 823-830. DOI: 10.5220/0010806700003124

in Bibtex Style

@conference{visapp22,
author={Tiago Silva and Luís Magalhães and Manuel Ferreira and Salik Ram Khanal and Jorge Silva},
title={Tracking 3D Deformable Objects in Real Time},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={823-830},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010806700003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Tracking 3D Deformable Objects in Real Time
SN - 978-989-758-555-5
AU - Silva T.
AU - Magalhães L.
AU - Ferreira M.
AU - Khanal S.
AU - Silva J.
PY - 2022
SP - 823
EP - 830
DO - 10.5220/0010806700003124
PB - SciTePress